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highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to predict the impact of mutations on genes in the avian flu virus and the viral host which
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John Williamson, and Dr Sebastian Stein. The job requires the proven ability to develop novel theory and build and evaluate working interactive prototypes involving complex computational models
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of classification algorithms Correlate/Integrate In Vivo and Ex Vivo metabolite analysis to understand the key metabolic pathways in different tumour types and subtypes Identify and harmonise MRI and MRS acquisition
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inversion techniques and signal processing. Strong programming skills, Proficiency in scientific computing (e.g. Python, MATLAB, or similar) for algorithm development and data handling. Experience with sensor
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HiPerBreedSim project. In this role, you will leverage recent advances in working with ancestral recombination graphs (ARGs) to develop algorithms and code for simulating population genomic data, including
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algorithms might support the wider integration of, and uptake of, renewable energy technologies for particular use cases and considering a variety of perspectives (technical/policy/social/economic). You will
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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, the appointed candidate will work closely with the line manager to develop novel control algorithms in EAP soft robotics combining Gaussian Predictors, hands-on laboratory experiments and JULIA computing
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their own research programme as well as support in the delivery of AI upskilling and expertise transfer to government. What you would be doing The objectives for the role are: to deliver ground-breaking
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are not limited to: network architecture design for NTN and terrestrial network (TN) convergence, intelligent traffic steering algorithms between TN and NTN, orchestration of TN/NTN resources for end-to-end